Right to Read and Play: How are Ontario Kindergarten Educators Currently Integrating Alphabetics into Play-Based Learning?
Bibliographic record
Abstract
Learning to read involves the development of many skills, including alphabetics, fluency, and comprehension. Alphabetics are the foundation of early reading and serve as precursors to the development of fluency and comprehension skills. Research evidence has accumulated in support of the direct instruction of alphabetics; however, direct instruction is sometimes perceived to be in opposition to constructivist approaches such as play-based learning. This study examined how Ontario Kindergarten teachers integrated the teaching of alphabetics within the context of a play-based learning curriculum. Observational video data collected across 21 demographically diverse kindergarten classrooms in Ontario were deductively coded for type of alphabetics and instructional approach. Results demonstrate that educators use both direct instruction and teacher-facilitated play to support students’ development of early literacy skills (e.g., phonological awareness, phonemic awareness, alphabet knowledge, and phonics). The results suggest that developmentally appropriate literacy instruction in kindergarten can include both direct instruction and teacher-facilitated play.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".